Search results for "Networks"
showing 10 items of 3260 documents
Wireless Sensor Network Software Design Rules
2014
Bezvadu sensoru tīkli (BST) pēdējā desmitgadē sevi pierādījusi kā daudzsološa pieeja viedā planētas izpētē, piedāvājot risinājumus savvaļas dabas un dzīvnieku novērošanai, drošības sistēmu izstrādei, pacientu veselības stāvokļa kontrolei, industriālajai ražošanai un citām sfērām. Sensoru tīklu savstarpējai savietojamībai un programmatūras pārnesamībai trūkst vienotu standartu un vienotas metodoloģijas. Eksistē ievērojams skaits operētājsistēmu (OS), virtuālo mašīnu, vaicājumu valodu un citu rīku sensoru tīklu programmēšanai. Ir izstrādāta virkne dažādu komunikācijas protokolu. Tomēr praksē sensoru tīklu projektētāji un programmētāji joprojām saskaras ar problēmām jaunu platformu un lietotņu…
Mašīnmācīšanās uzdevumu risināšanai interaktīvās tekstuālās vidēs
2021
Interaktīvas tekstuālas piedzīvojumu spēles var izmantot, lai pārbaudītu mašīnmācīšanās aģentu spējas tikt galā ar dažādiem izaicinājumiem, kas saistīti ar dabiskās valodas izpratni, problēmu risināšanu un atbilžu meklēšanu, vai tādas darbības izvēles stratēģiju apgūšana, kas vispārinās uz iepriekš nesastaptām vidēm. TextWorld platforma ir šādiem pētījumiem domāts ietvars un palīgrīki, ar kuru palīdzību var darbināt daudzas iepriekšpublicētas teksta piedzīvojumu spēles, vai arī definēt un ģenerēt jaunas spēles, dažādās sarežģītības pakāpēs un gandrīz bezgalīgās variācijās. Šajā darbā aprakstīta tāda algoritmiska orākula (oracle) ieviešana, kas var veiksmīgi atrisināt spēles no 3 dažādām iep…
Mašīnmācīšanās pielietojums sporta notikumu prognozēšanā
2017
Dažādu notikumu prognozēšana cilvēcei ir vienmēr bijusi aktuāla. Mūsdienās ir attīstījušās tehnoloģijas, lai to būtu iespējams paveikt balstoties uz pagātnes datiem. Darbā tiek apskatīta sporta notikumu prognozēšana, konkrēti futbola maču iznākumi. Tiek apskatītas vairākas mašīnmācīšanās metodes, kas būtu piemērotākās šī uzdevuma veikšanai. Tiek realizēti un optimizēti divi multi-slāņu perceptrona tīkli un viens vairākkārtējā neironu tīkla, konkrēti LSTM algoritms. Ar tiem tiek veikta simulācija izmantojot reālus datus. Vienā no simulācijām tiek sasniegts pozitīvs rezultāts, sezonas laikā algoritms gūst 65% peļņu.
The interaction between social media, knowledge management and service quality: A decision tree analysis
2020
The existing literature fails to identify to which extent the utilization of social media could be relevant for increasing the effectiveness of knowledge management, in respect to overall business operations. In order to shed some light on this area we define three goals. Firstly, we investigate to what extent the different activities of clients on social media (SM), are important to the processes of knowledge management (KM) in companies. Secondly, we examine to what extent KM functions can be relevant in attaining the quality of IT services. Thirdly, we analyze to what extent KM mediates between SM and the quality of IT services, that is, which client activities on SM should be formalised…
LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets
2015
International audience; There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a mo…
A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis
2014
Failure Mode and Effects Analysis (FMEA) is a systematic method for procedure analyses and risk assessment. It is a structured way to identify potential failure modes of a product or process, probability of their occurrence, and their overall effects. The basic purpose of this analysis is to mitigate the risk and the impact associated to a failure by planning and prioritizing actions to make a product or a process robust to failure. Effective manufacturing and improved quality products are the fruits of successful implementation of FMEA. During this activity valuable knowledge is generated which turns into product or process quality and efficiency. If this knowledge can be shared and reused…
Some recent contributions to routing and location problems
2003
CORAL 2003, a Conference on Routing and Location, washeld in Puerto de la Cruz (Tenerife, Spain) from February24–26, 2003. A wonderful place, close to the black sand ofthe beach, and a nice temperature welcomed a group ofsenior and young researchers from Canada, England,France, Germany, and Spain. Social activities were alsoprovided and sponsored by the Cabildo Insular de Tenerife(the local government) and TITSA (the public bus transpor-tation company on the island). The conference corre-sponded to the third annual meeting of a research project,funded by the Spanish Ministry of Science and Technology,developing a Decision Support System for Vehicle Routingand Facility Location Problems (SAD…
A Simple and Efficient Deep Learning-Based Framework for Automatic Fruit Recognition
2022
Accurate detection and recognition of various kinds of fruits and vegetables by using the artificial intelligence (AI) approach always remain a challenging task due to similarity between various types of fruits and challenging environments such as lighting and background variations. Therefore, developing and exploring an expert system for automatic fruits’ recognition is getting more and more important after many successful approaches; however, this technology is still far from being mature. The deep learning-based models have emerged as state-of-the-art techniques for image segmentation and classification and have a lot of promise in challenging domains such as agriculture, where they can …
A sentence based system for measuring syntax complexity using a recurrent deep neural network
2018
In this paper we present a deep neural network model capable of inducing the rules that identify the syntax complexity of an Italian sentence. Our system, beyond the ability of choosing if a sentence needs of simplification, gives a score that represent the confidence of the model during the process of decision making which could be representative of the sentence complexity. Experiments have been carried out on one public corpus created specifically for the problem of text-simplification.
A recurrent deep neural network model to measure sentence complexity for the Italian Language
2019
Text simplification (TS) is a natural language processing task devoted to the modification of a text in such a way that the grammar and structure of the phrases is greatly simplified, preserving the underlying meaning and information contents. In this paper we give a contribution to the TS field presenting a deep neural network model able to detect the complexity of italian sentences. In particular, the system gives a score to an input text that identifies the confidence level during the decision making process and that could be interpreted as a measure of the sentence complexity. Experiments have been carried out on one public corpus of Italian texts created specifically for the task of TS…